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mantis
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A package to annotate protein sequences
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# MANTIS  This tool can be used for protein function annotation, it is a standalone tool that uses HMMER or Diamond to match sequences against multiple reference datasets. It accepts as input an aminoacids sequence fasta. The main goals of this tool are to: - consider multiple protein domains - annotate with taxonomy resolution - use different reference datasets and provide a consensus annotation - be easy to setup and customize - scale well with multiple samples and/or metagenomes If you have only loose reads, you need to assemble them first; when you have assembled reads/genomes you need to predict the protein coding regions (gene prediction - e.g. prodigal) to convert your data into a protein fasta that Mantis can then use. **MANTIS IS NO LONGER IN ACTIVE DEVELOPMENT**, but I'm still maintaining it. I will try to answer any issues and fix any problems as soon as possible (usually over the weekend). **Mantis is compatible with genomes and metagenomes.** - [Installation](#installation) - [Functions](#functions) - [Further details](#further-details) Current release info ==================== | Name | Downloads | Version | Platforms | Latest release | |-----------------------------------------------------------------------------------------------------------------------| --- |---|---|---| | [](https://anaconda.org/bioconda/mantis_pfa) | [](https://anaconda.org/bioconda/mantis_pfa) | [](https://anaconda.org/bioconda/mantis_pfa) | [](https://anaconda.org/bioconda/mantis_pfa) | [](https://anaconda.org/bioconda/mantis_pfa) | # Citation If you use Mantis, please make sure you cite the respective paper https://doi.org/10.1093/gigascience/giab042 # Wiki Do you have any questions you can't find the answer to in here? Please read the [wiki](https://github.com/PedroMTQ/mantis/wiki). Still can't find the answer? Just post an issue and I'll answer as soon as possible! # Workflow overview  # Installation 1. `conda install -c conda-forge -c bioconda mantis_pfa` 2. `mantis setup` Mantis is now ready to run with: `mantis run -i target_faa` **Mantis can only run on Linux or MacOS systems. If you want to run Mantis on MacOS make sure you use python 3.7** # Customization Custom references can be added in **config/MANTIS.cfg** by adding their absolute path or folder path, for example: custom_ref=/path/to/ref_folder/file.hmm custom_ref=/path/to/ref_folder/file.dmnd custom_ref=/path/to/ref_folder/ Alternatively you may add them to the **custom_refs** folder, for example: Mantis/References/Custom_references/custom1/custom1.hmm Mantis/References/Custom_references/custom2/custom2.dmnd You may also redifine the **custom_refs** folder path by adding your preferred path to `custom_refs_folder` in the **config/MANTIS.cfg** file, for example: custom_refs_folder=path/to/custom_refs/ To integrate metadata, each custom reference folder should contain a `metadata.tsv` file - see [Custom References](https://github.com/PedroMTQ/mantis/wiki/Configuration#custom-references) for more details. ### Functions **1. Help** ```` mantis -h ```` **2. Setup databases** ```` mantis setup ```` **3. Check installation** ```` mantis check ```` **4. Check SQL metadata files** ```` mantis check_sql ```` **5. Annotate one sample** ```` mantis run -i target.faa -o output_folder-od organism_details -et evalue_threshold -ov overlap_value -mc custom_MANTIS.cfg ```` *example*: `mantis run -i mantis/tests/test_sample.faa -od "Escherichia coli"` **6. Annotate multiple samples** ```` mantis run -i target.tsv -o output_folder -et evalue_threshold -ov overlap_value -mc custom_MANTIS.cfg ```` *example*: `mantis run -i mantis/tests/test_file.tsv` ### Output files There are 3 output files: - `output_annotation.tsv`, which has all hits and their coordinates and e-values; - `integrated_annotation.tsv` which has all hits, their coordinates and e-value, as well as the respective hit metadata; - `consensus_annotation.tsv` which has all hits and their respective metadata from the best reference sources consensus. The first two files can have the same query sequence in several lines (query sequence/reference source) while the `consensus_annotation.tsv` will only have one line per query sequence (consensus/query). **GFF formatted output files can also be generated, as well as KEGG modules completeness tsv. Please see the [Output](https://github.com/PedroMTQ/mantis/wiki/output) page for information on the additional output files.** # Further details * [Configuration](https://github.com/PedroMTQ/mantis/wiki/Configuration) * [Installation](https://github.com/PedroMTQ/mantis/wiki/Configuration#installation) * [Setting your own paths](https://github.com/PedroMTQ/mantis/wiki/Configuration#setting-your-own-paths) * [Custom References](https://github.com/PedroMTQ/mantis/wiki/Configuration#custom-references) * [Setting references weight](https://github.com/PedroMTQ/mantis/wiki/Configuration#setting-references-weight) * [Functionalities](https://github.com/PedroMTQ/mantis/wiki/Functionalities) * [Setup databases](https://github.com/PedroMTQ/mantis/wiki/Functionalities#setup-databases) * [Check installation](https://github.com/PedroMTQ/mantis/wiki/Functionalities#check-installation) * [Annotating one sample](https://github.com/PedroMTQ/mantis/wiki/Functionalities#annotate-one-sample) * [Annotating multiple samples](https://github.com/PedroMTQ/mantis/wiki/Functionalities#annotate-multiple-samples) * [Annotating Metagenomes](https://github.com/PedroMTQ/mantis/wiki/Functionalities#annotating-metagenomes) * [Output](https://github.com/PedroMTQ/mantis/wiki/Output) * [Additional information](https://github.com/PedroMTQ/mantis/wiki/Additional-information) * [Reference data](https://github.com/PedroMTQ/mantis/wiki/Additional-information#reference-data) * [Copyright](https://github.com/PedroMTQ/mantis/wiki/Copyright) # License and copyright This project is available under the [MIT license](https://github.com/PedroMTQ/mantis/wiki/Copyright). # References and acknowledgements > Queirós, Pedro, Novikova, Polina, Wilmes, Paul and May, Patrick. "Unification of functional annotation descriptions using text mining" Biological Chemistry, vol. , no. , 2021. https://doi.org/10.1515/hsz-2021-0125 > > S. R. Eddy. HMMER: biosequence analysis using profile hidden Markov models. HMMER v.3.2.1 www.hmmer.org > > Buchfink, B., Xie, C., & Huson, D. H. (2015). Fast and sensitive protein alignment using DIAMOND. Nature methods, 12(1), 59–60. https://doi.org/10.1038/nmeth.3176 > > eggNOG 5.0: a hierarchical, functionally and phylogenetically annotated orthology resource based on 5090 organisms and 2502 viruses. Jaime Huerta-Cepas, Damian Szklarczyk, Davide Heller, Ana Hernández-Plaza, Sofia K Forslund, Helen Cook, Daniel R Mende, Ivica Letunic, Thomas Rattei, Lars J Jensen, Christian von Mering, Peer Bork Nucleic Acids Res. 2019 Jan 8; 47(Database issue): D309–D314. https://doi.org/10.1093/nar/gky1085 > > The Pfam protein families database in 2019: S. El-Gebali, J. Mistry, A. Bateman, S.R. Eddy, A. Luciani, S.C. Potter, M. Qureshi, L.J. Richardson, G.A. Salazar, A. Smart, E.L.L. Sonnhammer, L. Hirsh, L. Paladin, D. Piovesan, S.C.E. Tosatto, R.D. Finn Nucleic Acids Research (2019) https://doi.org/10.1093/nar/gky995 > > Aramaki T., Blanc-Mathieu R., Endo H., Ohkubo K., Kanehisa M., Goto S., Ogata H. KofamKOALA: KEGG ortholog assignment based on profile HMM and adaptive score threshold. Bioinformatics. 2019 Nov 19. pii: btz859. https://doi.org/10.1093/bioinformatics/btz859. > > Lu S, Wang J, Chitsaz F, Derbyshire MK, Geer RC, Gonzales NR, Gwadz M, Hurwitz DI, Marchler GH, Song JS, Thanki N, Yamashita RA, Yang M, Zhang D, Zheng C, Lanczycki CJ, Marchler-Bauer A. CDD/SPARCLE: the conserved domain database in 2020. Nucleic Acids Res. 2020 Jan 8;48(D1):D265-D268. doi: 10.1093/nar/gkz991. PMID: 31777944; PMCID: PMC6943070. > > Fast genome-wide functional annotation through orthology assignment by eggNOG-mapper. Jaime Huerta-Cepas, Kristoffer Forslund, Luis Pedro Coelho, Damian Szklarczyk, Lars Juhl Jensen, Christian von Mering and Peer Bork. Mol Biol Evol (2017). [doi:10.1093/molbev/msx148](https://doi.org/10.1093/molbev/msx148) > > Saier MH, Reddy VS, Moreno-Hagelsieb G, Hendargo KJ, Zhang Y, Iddamsetty V, Lam KJK, Tian N, Russum S, Wang J, Medrano-Soto A. The Transporter Classification Database (TCDB): 2021 update. Nucleic Acids Res. 2021 Jan 8;49(D1):D461-D467. doi: 10.1093/nar/gkaa1004. PMID: 33170213; PMCID: PMC7778945.
